Aon Risk Services, Inc. of Maryland

Verint Americas Inc.

Timothy Seegan

Samuel Cameron Fleming

Jared Dirk Sol

Scott Buzan

David Craig Andrews

John E Bradley, Iii

Ian Roy Beaver

Lewis C Lee

Christopher Ali Mirabzadeh

Joseph Henderson Ashmore

Systems and methods for generation and use of document analysis architectures are disclosed. A model builder component may be utilized to receiving user input data for labeling a set of documents as in class or out of class. That user input data may be utilized to train one or more classification models, which may then be utilized to predict classification of other documents. Trained models may be incorporated into a model taxonomy for searching and use by other users for document analysis purposes.

Document analysis architecture

Hybrid natural language understanding (NLU) systems and methods are provided that capitalize on the strengths of the rule-based models and the statistical models, lowering the cost of development and increasing the speed of construction, without sacrificing control and accuracy. Two models are used for intent recognition, one statistical and one rule-based. Both models define the same set of intents, but the rule-based model is devoid of any grammars or patterns initially. Each model may or may not be hierarchical in that it may be composed of a set of specialized models that are in a tree form or it may be just a singular model.

Hybrid natural language understanding

Growing community of inventors

Spokane, WA, United States of America

Timothy Seegan